Course Cancer Epidemiology using the Danish Clinical Cancer Databases

ECTS: 3.2

Course leader: Deirdre Cronin Fenton

Language: English

Graduate school: Faculty of Health

Graduate program: ClinFO

Course fee: 3,840.00 DKK

Status: Course is open for application

Semester: Spring 2023

Application deadline: 15/05/2023

Start date: 12/06/2023

Administrator: Thilde Møller Risgaard

The course C245/08 Cancer Epidemiology using the Danish Clinical Cancer Databases is being offered by the Graduate School of Health, Aarhus University, 2023.

Criteria for participation: University degree in medicine, dentistry, nursing, or master’s degree in other fields and/or postgraduate research fellows (PhD students and research-year medical students).

Recommended knowledge for participation: Basics of epidemiology (undergraduate level), oncology/cancer research knowledge and some knowledge of statistics. Knowledge of a statistical program – examples will be presented in STATA or R.

Aim: To provide students with an overview on how to take a research idea through to implementing, analysing, and interpreting an epidemiologic study using the Danish Clinical Cancer Databases, and Denmark’s network of medical and population-based registries. Each concept will be introduced in a lecture. Through a combination of exercises and computer labs, students will be provided with guidance on implementing, analysing and interpreting studies using data from the clinical cancer databases. Students are not required to complete an exam at the end of the course.

Target group: Ph.D. students working/planning to work on data from the Danish Clinical Cancer Databases.

Learning outcomes: 

  1. Identify and design a clinical epidemiologic research study using the Danish Clinical Cancer Databases – comparing and contrasting study designs in order to suitably address a research question
  2. Identifying and ascertaining data from the Clinical Cancer Databases
  3. Assessing study validity and implementing validity checks
  4. Data analysis including data cleaning and implementing survival analysis using Stata
  5. Evaluating study findings, interpreting and reporting study findings

Workload: The full workload of the course is expected to be 80 hours.

Content: The course includes lectures, exercises and computer labs on the following:

Monday am

What data can we use?

Overview of the data permissions, data sources, data variables

Introduction to the Danish Clinical Cancer Databases & main Danish health and administrative registries. Some examples:

The Danish Breast Cancer Cooperative Group (several research examples)

GROUP WORK: Students are assigned to a research topic & begin to work on assigned research topic

Dee Cronin Fenton


Monday pm

Data view and visualization of study design

Computer lab: Data cleaning and preparation of data for statistical analyses

Signe Sørup

Katrine B Nielsen

Tuesday am

Can we trust the data?

Approaches to ensure data validity? How to deal with incomplete data; how to incorporate validity checks via validation studies; how to minimize bias in the design phase; approaches to sensitivity analyses

GROUP WORK: Students work on assigned research topic

Mette Nørgaard


Tuesday pm

Computer lab: Conducting a validation study

Therese Grønborg

Kirsten Woolpert

Wednesday am

How can we address a research question?

Epidemiological study designs (Identify, describe, compare and contrast study designs to address a research question).

Defining the study population; measure of exposure; measures of association

KEA Research papers

GROUP WORK: Students work on assigned research topic

Julie Schmidt

Kirsten Woolpert

Cathrine Hjorth


Wednesday pm

Introduction to survival analyses

Computer lab: Survival analysis

Katrine B. Nielsen

Signe Sørup

Thursday am

Evaluating whether an observed association suggests a causal association: Can we trust the analysis?

Dealing with confounding, effect measure modification, and bias

Restriction, stratification, standardization, multivariate modelling

(Immortal person-time bias in cancer prognosis studies)

Examples from several KEA research papers using DBCG data

Dee Cronin Fenton


Thursday pm

GROUP WORK: Students work on assigned research topic – preparation of presentation for Friday

Julie Schmidt

Friday am

How can we interpret and present our findings?

STROBE and STREGA guidelines; p-values

Evaluating whether an observed association suggests a causal association

Contextualizing research findings Example of KEA reviews (Dee – CYP2D6 & statins reviews)

GROUP WORK: Students work on assigned research topic

Dee Cronin Fenton

Mette Nørgaard


Friday pm

GROUP WORK: Students present assigned research topic

(10 minute presentation, 5 minute Q&A) (4 groups of 3-4)

Dee Cronin Fenton

Mette Nørgaard


Instructors: Signe Sørup, Ph.D., Katrine Bødkergaard Nielsen, M.Sc., Julie Schmidt, DPhil, Kirsten Woolpert, M.Sc., Cathrine Hjorth, Ph.D., Therese Grønborg, Ph.D.

Venue: Aarhus University, Aarhus

Participation in the course is without cost for:

  • PhD students, Health Research Year students and Health Research Honours Programme students from Aarhus University
  • PhD students enrolled at partner universities of the Nordoc collaboration
  • PhD students from other institutions in the open market agreement for PhD courses


Course dates:

  • 12 June 2023 09:00 - 15:30
  • 13 June 2023 09:00 - 15:30
  • 14 June 2023 09:00 - 15:30
  • 15 June 2023 09:00 - 15:30
  • 16 June 2023 09:00 - 15:30